RCSB PDB Explorer MCP Server

RCSB PDB Explorer MCP Server

The RCSB PDB Explorer is an MCP server that lets conversational AI models, such as Claude, access the vast, structured repository of macromolecular structures housed by the RCSB Protein Data Bank. By exposing a GraphQL‑based interface, the server turns raw PDB data into easily consumable queries that an assistant can interpret and answer in natural language. This eliminates the need for developers to write custom parsers or maintain local copies of the database, enabling instant retrieval of experimental details, sequence information, and computed structure models.

For developers building AI‑powered research tools, the server is a bridge between language models and high‑value scientific data. Instead of feeding static text or pre‑formatted tables to a model, the assistant can issue precise GraphQL queries that return only the fields required for a particular question. This reduces latency, keeps responses focused, and preserves privacy by transmitting only the necessary data over a secure WebSocket connection. The MCP protocol ensures that the assistant can discover available queries, validate input parameters, and receive structured results without hard‑coding endpoints.

Key capabilities include:

• Entry lookup: Retrieve metadata such as title, experimental method, resolution, and authors for any PDB ID.
• Molecule and sequence retrieval: Access atom lists, residue sequences, and ligand information directly from the database.
• Computed structure models: Query AlphaFold or other predictive models that are linked to PDB entries.
• GraphQL introspection: The server exposes a full schema, allowing the assistant to discover available fields and construct queries on the fly.

Typical use cases span academic research, drug discovery, and educational tools. A computational chemist can ask the assistant to “show me all cryo‑EM structures of hemoglobin with resolution better than 3 Å,” and the server will return a concise list. A biology instructor might embed the assistant in a classroom app to let students query real protein structures while learning about molecular biology concepts. In drug design pipelines, an AI can automatically pull binding site information for a target protein and feed it into downstream docking software.

Integration is straightforward: developers add the server URL to their AI platform (e.g., Cloudflare AI Playground or Claude Desktop) and grant the assistant access. Once connected, the model can issue tool calls that are routed through MCP to the RCSB server, receive structured JSON responses, and incorporate them into its replies. This seamless workflow lets developers focus on higher‑level application logic while leveraging the most up‑to‑date protein data without maintaining complex infrastructure.

In summary, the RCSB PDB Explorer MCP server empowers AI assistants to tap directly into a premier biological database, offering precise, real‑time access to protein structure information that is invaluable for research, development, and education.